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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Green's Function Wind Turbine Induction Model That Incorporates Complex Inflow Conditions

ABSTRACT In this work, we develop a new analytical turbine induction model that can incorporate complex inflow conditions including cases where the wind velocity and temperature profiles can vary as functions of height. This induction model is derived from the linearized Navier–Stokes and leads to a second‐order ODE that can be solved using a Green's function formulation. The corresponding Green's function for several configurations are found including the infinite domain, semi‐infinite domain with ground plane, and a power law velocity inflow profile. The results of this approach are then compared with simulations of the turbine induction field using the AMR‐Wind CFD solver with a uniformly loaded actuator disk model. These comparisons show that the Green's function approach captures the centerline blockage, three‐dimensional blockage flow field, and streamwise velocity slow down, with very good agreement for lower thrust conditions and at larger distances away from rotor disk. The effects of shear on the turbine blockage were also compared using a power law inflow profile, and we show that this approach matches the CFD predictions for the cases considered.

17 WIND ENERGY↗
DOE OSTI2023

A Three-Dimensional, Analytical Wind Turbine Wake Model: Flow Acceleration, Empirical Correlations, and Continuity

A new, three-dimensional, analytical, steady-state wake model is presented that includes local flow acceleration near the rotor, improving the wake description compared to existing models. Wake structures such as the momentum deficit and regions of accelerated flow are concisely described with compound and normal Gaussian functions. Large-eddy simulations (LES) are used as training data to develop the model using two in-line turbines under various inflow conditions parameterized by hub-height wind speed and turbulence intensity. Mass conservation is considered by fixing two components of the wake velocity model and optimizing the third to best satisfy continuity; after which, the model performs comparably if not better than existing work with regards to both relative error and mass consistency. The final model demonstrates a high degree of flexibility, making use of empirical correlations to scale across different inflow conditions. The inclusion of these effects is capable of revealing unused opportunities for enhanced power generation by aligning wake trajectories with these regions of accelerated flow.

modeling↗
DOE OSTI2025

Investigation of Main Bearing Fatigue Estimate Sensitivity to Synthetic Turbulence Models Using a Novel Drivetrain Model Implemented in OpenFAST

ABSTRACT A coupled medium‐fidelity drivetrain model is developed and implemented in OpenFAST for a 10‐MW land‐based reference turbine. The implementation is verified against a fully coupled multibody wind turbine model, including a detailed drivetrain. The new model can simultaneously and accurately estimate main bearing loads and represent elastic bending of the drivetrain. It has low computational cost and is useful for early design phases, sensitivity analyses and complex systems like wind farms (where computational expense must be expended elsewhere). Here, the model is implemented for a monopile offshore wind turbine and used to investigate the sensitivity of main bearing basic rating life to different synthetic turbulence models. Large‐eddy simulations (LES) targeting stable, neutral, and unstable atmospheric conditions at below‐, near‐ and above‐rated wind speeds are used as a reference. The turbulence models recommended by the International Electrotechnical Commission, the Mann spectral tensor model, and the Kaimal spectral model with exponential coherence are fitted to the LES data. Additionally, a constrained turbulence generator, PyConTurb (short for Python Constrained Turbulence ), based on LES data, is applied in the aero‐hydro‐servo‐elastic simulations. Taking PyConTurb as the baseline, the Kaimal model significantly underestimates fatigue of the downwind main bearing, with between 10% and 40% less damage. The Mann model also underestimates the downwind main bearing fatigue by up to 30%. The upwind main bearing damage is driven by mean loads, and differences between models are less significant, although the trends are similar. Reasons for these discrepancies are investigated and attributed to differences in spatial and temporal variations among the turbulence models.

17 WIND ENERGY↗
DOE OSTI2020

Multi-Scale Simulation of Wind Farm Performance during a Frontal Passage

Predicting the response of wind farms to changing flow conditions is necessary for optimal design and operation. Here in this work, simulation and analysis of a frontal passage through a utility scale wind farm is achieved for the first time using a seamless multi-scale modeling approach. A generalized actuator disk (GAD) wind turbine model is used to represent turbine–flow interaction, and results are compared to novel radar observations during the frontal passage. The Weather Research and Forecasting (WRF) model is employed with a nested grid setup that allows for coupling between multi-scale atmospheric conditions and turbine response. Starting with mesoscale forcing, the atmosphere is dynamically downscaled to the region of interest, where the interaction between turbulent flows and individual wind turbines is simulated with 10 m grid spacing. Several improvements are made to the GAD model to mimic realistic turbine operation, including a yawing capability and a power output calculation. Ultimately, the model is able to capture both the dynamics of the frontal passage and the turbine response; predictions show good agreement with observed background velocity, turbine wake structure, and power output after accounting for a phase shift in the mesoscale forcing. This study demonstrates the utility of the WRF-GAD model framework for simulating wind farm performance under complex atmospheric conditions.

17 WIND ENERGY↗
DOE OSTI2023

RAAW

High-fidelity wind turbine modeling advances necessitate model validation datasets of equally high fidelity. The Rotor Aerodynamics, Aeroelastics & Wake (RAAW) project was designed to address this need. This three-year project runs from October 2021 through October 2024 starting with a field data collection period followed by model validation activities. RAAW is a partnership between GE Renewable Energy and the United States Department of Energy (DOE) through the National Renewable Energy Laboratory (NREL) and Sandia National Laboratories. The field experiment is designed to make detailed measurements of the inflow, wind turbine response, and the resulting wake. The experimental dataset will be suitable for validating wind turbine models across the fidelity spectrum from actuator disk methods to blade-resolved codes.

17 WIND ENERGY↗
DOE OSTI2025

A critical verification of beam and shell models of wind turbine blades

Ever-increasing wind turbine size has challenged predictive capabilities on several fronts. Here, to address part of the blade structural modeling uncertainty, a systematic model fidelity comparison study was conducted on commonly used finite elements. pyNuMAD was utilized to create beam, shell, and solid models of a 100 m long blade undergoing large static deflections. The solid model avoided the use of layered-solid elements by resolving core and facesheet layers. An unprecedented model with 73.7 million elements revealed insights that have never been possible from prior experimental and numerical studies. As compared to the solid element model, the tip deflection from the shell and beam model was found to be about 2% and 4.3% too low, respectively. The twist from the beam model was found to be about 5.6% too high, while the twist from shell model was 24% too low, though improvement was demonstrated with mesh refinement. The beam model adhesive stresses were more accurate than the shell model. Out-of-plane stresses were of great significance near geometric and material discontinuities, and neither the shell nor beam model captured these effects well. Failure predictions from beam, shell, or layered-solid models are unlikely to be reliable at trailing edges, adhesives, ply-drops, spar-cap boundaries.

17 WIND ENERGY↗
DOE OSTI2026

Develop and verify soil/structure interaction for pile/foundation interaction

Phase II of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was used to verify the implementation of a new soil-structure interaction (SSI) model for use within offshore wind turbine modeling software. The REDWIN Macro-element model implemented and verified in this study enables a computationally efficient way to model the linear and nonlinear SSI problem, including hysteretic damping, of a monopile structure. The modeling approach was integrated into several modeling tools and a series of increasingly complex simulations was conducted using the IEA 10MW reference turbine mounted on a monopile support structure to verify the coupling between the tools and the REDWIN Macro-element SSI model. This campaign includes only numerical verification between various software and modeling approaches so no experimental measurements are available. The load cases (LC) considered include: LC1 – static response of the tower and substructure LC2 – frequency and mode-shape analysis of the tower and substructure LC3 – response of the tower and substructure due to wind-only loading LC4 – response of the tower and substructure due to wave-only loading LC5 – response of the tower and substructure due to wind and wave loading. Detailed properties of the modeled system are found in the following reference, “Bergua, Roger, Amy Robertson, Jason Jonkman, and Andy Platt. 2021. "Specification Document for OC6 Phase II: Verification of an Advanced Soil-Structure Interaction Model for Offshore Wind Turbines.” Golden, CO: National Renewable Energy Laboratory. NREL/TP-5000-79938. https://www.nlr.gov/docs/fy21osti/79938.pdf. Details on the results from the OC6 Phase II project can be found in the following reference, “Bergua R, Robertson A, Jonkman J, et al. OC6 Phase II: Integration and verification of a new soil–structure interaction model for offshore wind design.” Wind Energy. 2022;25(5):793-810. doi:10.1002/we.2698

17 WIND ENERGY↗
DOE OSTI2020

Electro-mechanical Modeling of Wind Turbine and Energy Storage Systems with Enhanced Inertial Response

In this paper, a coordinated control scheme for wind turbine generator (WTG) and supercapacitor energy storage system (ESS) is proposed for temporary frequency supports. Inertial control is designed by using generator torque limit considering the security of WTG system, while ESS releases its energy to compensate the sudden active power deficit during the recovery process of turbine rotor. WTG is modeled using the fatigue, aerodynamic, structure, turbulence (FAST) code, which identifies the mechanical loadings of the turbine and addresses electro-mechanical interactions in the wind energy system. A damping controller is augmented to the inertial control to suppress severe mechanical oscillations in the shaft and tower of the turbine during frequency supports. Furthermore, the result of small-signal stability analysis shows that the WTG-ESS tends to improve the stability of the whole multi-energy power grid. The major contributions of this paper will be validated by utilizing the proposed control method that combines the grid support capability and maintaining the integrity of structural design of the turbine for normal operations.

17 WIND ENERGY↗
DOE OSTI2024

NREL 15-kW: An Advanced Horizontal-Axis Reference Turbine for Distributed Wind

Distributed wind energy can play a significant role in the renewable energy landscape. A recent study conducted by the National Renewable Energy Laboratory (NREL) identified the lack of availability and utilization of reference wind turbine models as a major hindrance in the development of the distributed wind energy technology sector, even though such models are widely used in offshore and land-based wind research. Therefore, NREL is developing three reference wind turbine architectures, also called archetypes, for distributed wind energy applications. This paper describes the detailed design and modeling of the first of the three reference turbine archetypes, called the NREL 15-kW turbine. It is a passive-yaw, upwind turbine with a rated power of 15 kW.

17 WIND ENERGY↗
DOE OSTI2022

System Modeling Frameworks for Wind Turbines and Plants: Review and Requirements Specifications

System modeling frameworks for wind turbines and plants are used by research groups and industry to design wind energy systems that take into account key trade-offs across performance, cost, and reliability at both the turbine and plant level. The frameworks are exercised using a variety of multi-disciplinary design, analysis and optimization (MDAO) methods. To improve inter-operability and foster collaboration, this report proposes a classification system for the frameworks along dimensions of model fidelity and scope. The classification system is first motivated with reviews the state-of-the-art in the development of software frameworks for integrated wind turbine and plant simulation. Within each major wind turbine and power plant subsystem, a matrix is developed for the disciplines used and the fidelity levels with which each discipline can be modeled. The existing frameworks are then classified according to the matrix. Next, an ontology is proposed that will allow for standardizing how data is transferred between the most common discipline-fidelity combinations used in the frameworks. A common representation of data creates the ability to 1) share system descriptions and analysis results, supporting more transparent benchmarks and comparison, and 2) integrate models together into workflows within and across organizations for improving the efficiency and performance of wind turbine and power plant design processes. Ultimately, this integration leads to better overall wind energy system designs with high performance and low costs.

17 WIND ENERGY↗
DOE OSTI2024

Design Load Basis Guidance for Distributed Wind Turbines

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine. Nonetheless, the use of AM in the distributed wind (DW) industry sector is limited due to several challenges (Damiani, Davis, & Summerville, 2022). One of these challenges lies in the perceived complexity of generating a proper set of numerical simulations to extract and process the key outputs for component design and verification, and, ultimately, achieve certification. This makes it difficult to reliably predict the structural and performance response of small wind turbines. From the investigation carried out in (Damiani & Davis, 2022), it is apparent that many stakeholders in this sector believe that a comprehensive guide for developing a design load basis (DLB) for distributed wind turbines (DWTs) is necessary.

17 WIND ENERGY↗
DOE OSTI2024

Development of an Optimal Variable-Pitch Controller for Floating Axial-Flow Marine Hydrokinetic Turbines

This article discusses the development of an optimal variable-pitch controller for floating, axial-flow marine turbines. Recently, OpenFAST, an open-source wind turbine modeling tool, has been extended to model marine turbines. A controller is necessary to simulate marine turbines for different load cases using OpenFAST, which greatly impacts the performance of the energy system. Previous studies have designed controllers using a linearized model of the marine turbine, which can be time-consuming and require the expertise of a control engineer. In this study, we use an automated approach that uses generic models of the marine turbine to identify the controller gains, which can expedite the process of designing a controller. Using an optimizer to identify the control system parameters can additionally improve the controller's performance. The optimal controller tuned using such an approach results in a 20% reduction in the tower-base damage equivalent loading and better tracking of the rated generator speed and power.

axial flow↗
NASA NTRS1989

Model 0A wind turbine generator FMEA

The results of Failure Modes and Effects Analysis (FMEA) conducted for the Wind Turbine Generators are presented. The FMEA was performed for the functional modes of each system, subsystem, or component. The single-point failures were eliminated for most of the systems. The blade system was the only exception. The qualitative probability of a blade separating was estimated at level D-remote. Many changes were made to the hardware as a result of this analysis. The most significant change was the addition of the safety system. Operational experience and need to improve machine availability have resulted in subsequent changes to the various systems which are also reflected in this FMEA.

Klein, William E.↗
NASA NTRS1990

Model-OA wind turbine generator - Failure modes and effects analysis

The results failure modes and effects analysis (FMEA) conducted for wind-turbine generators are presented. The FMEA was performed for the functional modes of each system, subsystem, or component. The single-point failures were eliminated for most of the systems. The blade system was the only exception. The qualitative probability of a blade separating was estimated at level D-remote. Many changes were made to the hardware as a result of this analysis. The most significant change was the addition of the safety system. Operational experience and need to improve machine availability have resulted in subsequent changes to the various systems, which are also reflected in this FMEA.

Klein, William E.↗
DOE OSTI2022

2020 Awardee of Two Small Wind Turbine Certification and Listing Awards: QED

With support from the Competitiveness Improvement Project's Small Wind Turbine Certification and Listing awards, QED Wind Power LLC will expand their ability to manufacture and distribute their 20-kilowatt, small wind turbine model to larger national markets. QED Wind Power aims to achieve this by conducting and completing testing of their small wind turbine and achieve safety and performance certification and listing with support from the National Renewable Energy Laboratory. This fact sheet provides an overview of QEDWind Power's project, how the company will achieve the goals of the two awards, and how the project fits within the overall Competitiveness Improvement Project.

CIP↗